Coverage improvement for 5G new radio wireless communication network, such as for over-shooting cells

ABSTRACT

The described technology provides a system and method for determining, inter alia, if a serving cell in a cellular network is an over-shooter cell serving calls outside an intended or designed coverage area by searching for eligible neighbor cells in a search area bounded by an azimuth of a sector antenna of the serving cell. The serving cell is determined to be an over-shooter cell when, e.g., the distance between the serving cell and mobile devices associated with the calls is larger than the average distance between the serving cell and one or more closest neighbor cells in a list of eligible neighbor cells identified in the search area.

BACKGROUND

A cellular network is distributed over land areas called “cells”, eachserved by at least one fixed-location transceiver (typically three cellsites or base transceiver stations with 120 degree sector antennas).These base stations provide the cell with the network coverage which canbe used for transmission of voice, data, and other types of content. Insome radio access technologies (RATs), a cell typically uses a differentset of frequencies from neighboring cells, to avoid interference andprovide guaranteed service quality within each cell. When joinedtogether, these cells provide radio coverage over a wide geographicarea. This enables numerous portable transceivers to communicate witheach other and with fixed transceivers anywhere in the network even whensome of the transceivers are moving through more than one cell duringtransmission.

A service provider can locate infrastructure equipment (e.g., basestations or cell sites) geographically within a larger area such thatthe range of wireless communications may have some overlap and mayresemble a pattern such as a set of overlapping cells. The geographicarea for which individual infrastructure equipment can receive andtransmit radio communications to various mobile device is known as thecoverage of the individual infrastructure equipment. The quantity ofdevices or the data throughput that the individual infrastructureequipment can support within its geographic area may be considered thecapacity of the individual infrastructure equipment. Within a definedrange of individual infrastructure equipment, mobile devices mayexperience a different quality of radio signal communications accordingto the amount of power used for radio transmissions by the individualinfrastructure equipment, the orientation and capabilities of antennas,the terrain, buildings, interfering signals from other infrastructureequipment or other devices, and various other features that affect radiowave propagation.

To deliver service across a large geographic region, wirelesscommunication service providers may maintain networks of cells withoverlapping coverages and capacities. To ensure that the cellsadequately cover the intended or designed geographical regions, serviceproviders can perform drive testing to measure and assess the coverage,capacity, and Quality of Service (QoS) of the wireless communicationnetwork. Drive testing consists of using a motor vehicle containingmobile radio network air interface measurement equipment that can detectand record a wide variety of physical and virtual parameters of mobilecellular service in a given geographical area. By measuring what awireless network subscriber would experience in any specific area,wireless carriers can make directed changes to their networks thatprovide better coverage and service to their customers. Because drivetesting is expensive, time consuming, and resource intensive, thereexists a need for techniques to allow the service provider to improvethe coverage and capacity of wireless communication networks morerapidly and cost-effectively.

BRIEF DESCRIPTION OF THE DRAWINGS

Detailed descriptions of implementations of the present invention willbe described and explained through the use of the accompanying drawings.

FIG. 1 is a block diagram that illustrates a wireless communicationssystem.

FIG. 2 is a block diagram that illustrates an example of a computersystem in which at least some operations described herein can beimplemented.

FIG. 3 is a flowchart that illustrates an automated process foridentifying cells requiring coverage adjustment.

FIG. 4 is a flowchart that illustrates mapping serving cells togeo-located call information.

FIG. 5 is a table that illustrates representative cellular trafficinformation for automated coverage analysis.

FIG. 6 is a flowchart that illustrates determining a distance between aserving cell and one or more neighbor cells relevant for automatedcoverage analysis.

FIG. 7 is a flowchart that illustrates determining relevant neighborcells in a search area based on a serving cell antenna azimuth andbeamwidth.

FIG. 8 is a map that illustrates a cellular network with a serving cellaligned at a direct angle of transmission to a single neighbor cell.

FIG. 9 is a map that illustrates a cellular network with a serving cellnot aligned in a direct angle of transmission to a single neighbor cell.

FIG. 10 is a flowchart that illustrates identifying serving cells withover-shooter or under-shooter calls.

FIG. 11 is a map that illustrates a cellular network with over-shootercalls.

FIG. 12 is a map that illustrates a cellular network with under-shootercalls.

The technologies described herein will become more apparent to thoseskilled in the art from studying the Detailed Description in conjunctionwith the drawings. Embodiments or implementations describing aspects ofthe invention are illustrated by way of example, and the same referencescan indicate similar elements. While the drawings depict variousimplementations for the purpose of illustration, those skilled in theart will recognize that alternative implementations can be employedwithout departing from the principles of the present technologies.Accordingly, while specific implementations are shown in the drawings,the technology is amenable to various modifications.

DETAILED DESCRIPTION

The description and associated drawings disclose a coverage analysistool. In one aspect of the disclosed technology the coverage analysistool determines if a cell is an over-shooter cell by comparing an actualcoverage determined based on a distance between the cell and mobiledevices associated with extracted geolocated call data, and an expectedor designed coverage determined based on an average distance between thecell and one or more closest neighbor cells in a direction of coverageof the cell.

To determine the one or more closest neighbor cells in the direction ofcoverage of the cell that are used for the under-shooter determination,the coverage analysis tool determines an azimuth and beamwidth of asector antenna of the cell and determines a search area based on anoffset degree above and below the azimuth. If no neighbor cell is foundin the search area, the coverage analysis tool expands the search areaby an offset degree repeatedly until the search area is equal to thecell antenna beamwidth. If, after the maximum expansion to the sectorantenna beamwidth, eligible neighbor cells are not identified, thecoverage analysis tool uses a default inter-site distance to determinethe expected or designed coverage which is compared with the actualcoverage.

The description and associated drawings are illustrative examples andare not to be construed as limiting. This disclosure provides certaindetails for a thorough understanding and enabling description of theseexamples. One skilled in the relevant technology will understand,however, that the invention can be practiced without many of thesedetails. Likewise, one skilled in the relevant technology willunderstand that the invention can include well-known structures orfeatures that are not shown or described in detail, to avoidunnecessarily obscuring the descriptions of examples.

Wireless Communications System

FIG. 1 is a block diagram that illustrates a wireless telecommunicationsystem 100 (“system 100”) in which aspects of the disclosed technologyare incorporated. The system 100 includes base stations 102-1 through102-4 (also referred to individually as “base station 102” orcollectively as “base stations 102”). A base station is a type ofnetwork access node (NAN) that can also be referred to as a cell site, abase transceiver station, or a radio base station. The system 100 caninclude any combination of NANs including an access point, radiotransceiver, gNodeB (gNB), NodeB, eNodeB (eNB), Home NodeB or eNodeB, orthe like. In addition to being a WWAN base station, a NAN can be a WLANaccess point, such as an Institute of Electrical and ElectronicsEngineers (IEEE) 802.11 access point.

The NANs of a network formed by the system 100 also include wirelessdevices 104-1 through 104-8 (referred to individually as “wirelessdevice 104” or collectively as “wireless devices 104”) and a corenetwork 106. The wireless devices 104-1 through 104-8 can correspond toor include network entities capable of communication using variousconnectivity standards. For example, a 5G communication channel can usemillimeter wave (mmW) access frequencies of 28 GHz or more. In someimplementations, the wireless device 104 can operatively couple to abase station 102 over an LTE/LTE-A communication channel, which isreferred to as a 4G communication channel.

The core network 106 provides, manages, and controls security services,user authentication, access authorization, tracking, Internet Protocol(IP) connectivity, and other access, routing, or mobility functions. Thebase stations 102 interface with the core network 106 through a firstset of backhaul links 108 (e.g., S1 interfaces) and can perform radioconfiguration and scheduling for communication with the wireless devices104 or can operate under the control of a base station controller (notshown). In some examples, the base stations 102 can communicate, eitherdirectly or indirectly (e.g., through the core network 106), with eachother over a second set of backhaul links 110-1 through 110-3 (e.g., X1interfaces), which can be wired or wireless communication links.

The base stations 102 can wirelessly communicate with the wirelessdevices 104 via one or more base station antennas. The cell sites canprovide communication coverage for geographic coverage areas 112-1through 112-4 (also referred to individually as “coverage area 112” orcollectively as “coverage areas 112”). The geographic coverage area 112for a base station 102 can be divided into sectors making up only aportion of the coverage area (not shown). The system 100 can includebase stations of different types (e.g., macro and/or small cell basestations). In some implementations, there can be overlapping geographiccoverage areas 112 for different service environments (e.g.,Internet-of-Things (IoT), mobile broadband (MBB), vehicle-to-everything(V2X), machine-to-machine (M2M), machine-to-everything (M2X),ultra-reliable low-latency communication (URLLC), machine-typecommunication (MTC)), etc.

The system 100 can include a 5G network and/or an LTE/LTE-A or othernetwork. In an LTE/LTE-A network, the term eNB is used to describe thebase stations 102 and in 5G new radio (NR) networks, the term gNBs isused to describe the base stations 102 that can include mmWcommunications. The system 100 can thus form a heterogeneous network inwhich different types of base stations provide coverage for variousgeographical regions. For example, each base station 102 can providecommunication coverage for a macro cell, a small cell, and/or othertypes of cells. As used herein, the term “cell” can relate to a basestation, a carrier or component carrier associated with the basestation, or a coverage area (e.g., sector) of a carrier or base station,depending on context.

A macro cell generally covers a relatively large geographic area (e.g.,several kilometers in radius) and can allow access by wireless deviceswith service subscriptions with a wireless network service provider. Asindicated earlier, a small cell is a lower-powered base station, ascompared with a macro cell, and can operate in the same or different(e.g., licensed, unlicensed) frequency bands as macro cells. Examples ofsmall cells include pico cells, femto cells, and micro cells. Ingeneral, a pico cell can cover a relatively smaller geographic area andcan allow unrestricted access by wireless devices with servicesubscriptions with the network provider. A femto cell covers arelatively smaller geographic area (e.g., a home) and can providerestricted access by wireless devices having an association with thefemto cell (e.g., wireless devices in a closed subscriber group (CSG),wireless devices for users in the home). A base station can support oneor multiple (e.g., two, three, four, and the like) cells (e.g.,component carriers). All fixed transceivers noted herein that canprovide access to the network are NANs, including small cells.

The communication networks that accommodate various disclosed examplescan be packet-based networks that operate according to a layeredprotocol stack. In the user plane, communications at the bearer orPacket Data Convergence Protocol (PDCP) layer can be IP-based. A RadioLink Control (RLC) layer then performs packet segmentation andreassembly to communicate over logical channels. A Medium Access Control(MAC) layer can perform priority handling and multiplexing of logicalchannels into transport channels. The MAC layer can also use Hybrid ARQ(HARQ) to provide retransmission at the MAC layer, to improve linkefficiency. In the control plane, the Radio Resource Control (RRC)protocol layer provides establishment, configuration, and maintenance ofan RRC connection between a wireless device 104 and the base stations102 or core network 106 supporting radio bearers for the user planedata. At the Physical (PHY) layer, the transport channels are mapped tophysical channels.

As illustrated, the wireless devices 104 are distributed throughout thesystem 100, where each wireless device 104 can be stationary or mobile.A wireless device can be referred to as a mobile station, a subscriberstation, a mobile unit, a subscriber unit, a wireless unit, a remoteunit, a handheld mobile device, a remote device, a mobile subscriberstation, an access terminal, a mobile terminal, a wireless terminal, aremote terminal, a handset, a mobile client, a client, or the like.Examples of a wireless device include user equipment (UE) such as amobile phone, a personal digital assistant (PDA), a wireless modem, ahandheld mobile device (e.g., wireless devices 104-1 and 104-2), atablet computer, a laptop computer (e.g., wireless device 104-3), awearable (e.g., wireless device 104-4). A wireless device can beincluded in another device such as, for example, a drone (e.g., wirelessdevice 104-5), a vehicle (e.g., wireless device 104-6), an augmentedreality/virtual reality (AR/VR) device such as a head-mounted displaydevice (e.g., wireless device 104-7), an IoT device such as an appliancein a home (e.g., wireless device 104-8), a portable gaming console, or awirelessly connected sensor that provides data to a remote server over anetwork.

A wireless device can communicate with various types of base stationsand network equipment at the edge of a network including macroeNBs/gNBs, small cell eNBs/gNBs, relay base stations, and the like. Awireless device can also communicate with other wireless devices eitherwithin or outside the same coverage area of a base station viadevice-to-device (D2D) communications.

The communication links 114-1 through 114-11 (also referred toindividually as “communication link 114” or collectively as“communication links 114”) shown in system 100 include uplink (UL)transmissions from a wireless device 104 to a base station 102, and/ordownlink (DL) transmissions, from a base station 102 to a wirelessdevice 104. The downlink transmissions can also be called forward linktransmissions while the uplink transmissions can also be called reverselink transmissions. Each communication link 114 includes one or morecarriers, where each carrier can be a signal composed of multiplesub-carriers (e.g., waveform signals of different frequencies) modulatedaccording to the various radio technologies. Each modulated signal canbe sent on a different sub-carrier and carry control information (e.g.,reference signals, control channels), overhead information, user data,etc. The communication links 114 can transmit bidirectionalcommunications using FDD (e.g., using paired spectrum resources) or TDDoperation (e.g., using unpaired spectrum resources). In someimplementations, the communication links 114 include LTE and/or mmWcommunication links.

In some implementations of the system 100, the base stations 102 and/orthe wireless devices 104 include multiple antennas for employing antennadiversity schemes to improve communication quality and reliabilitybetween base stations 102 and wireless devices 104. Additionally oralternatively, the base stations 102 and/or the wireless devices 104 canemploy multiple-input, multiple-output (MIMO) techniques that can takeadvantage of multi-path environments to transmit multiple spatial layerscarrying the same or different coded data.

Computer System

FIG. 2 is a block diagram that illustrates an example of a computersystem 200 in which at least some operations described herein can beimplemented. As shown, the computer system 200 can include: one or moreprocessors 202, main memory 206, non-volatile memory 210, a networkinterface device 212, video display device 218, an input/output device220, a control device 222 (e.g., keyboard and pointing device), a driveunit 224 that includes a storage medium 226, and a signal generationdevice 230 that are communicatively connected to a bus 216. The bus 216represents one or more physical buses and/or point-to-point connectionsthat are connected by appropriate bridges, adapters, or controllers.Various common components (e.g., cache memory) are omitted from FIG. 2for brevity. Instead, the computer system 200 is intended to illustratea hardware device on which components illustrated or described relativeto the examples of the figures and any other components described inthis specification can be implemented.

The computer system 200 can take any suitable physical form. Forexample, the computing system 200 can share a similar architecture asthat of a server computer, personal computer (PC), tablet computer,mobile telephone, game console, music player, wearable electronicdevice, network-connected (“smart”) device (e.g., a television or homeassistant device), AR/VR systems (e.g., head-mounted display), or anyelectronic device capable of executing a set of instructions thatspecify action(s) to be taken by the computing system 200. In someimplementation, the computer system 200 can be an embedded computersystem, a system-on-chip (SOC), a single-board computer system (SBC) ora distributed system such as a mesh of computer systems or include oneor more cloud components in one or more networks. Where appropriate, oneor more computer systems 200 can perform operations in real-time, nearreal-time, or in batch mode.

The network interface device 212 enables the computing system 200 tomediate data in a network 214 with an entity that is external to thecomputing system 200 through any communication protocol supported by thecomputing system 200 and the external entity. Examples of the networkinterface device 212 include a network adaptor card, a wireless networkinterface card, a router, an access point, a wireless router, a switch,a multilayer switch, a protocol converter, a gateway, a bridge, bridgerouter, a hub, a digital media receiver, and/or a repeater, as well asall wireless elements noted herein.

The memory (e.g., main memory 206, non-volatile memory 210,machine-readable medium 226) can be local, remote, or distributed.Although shown as a single medium, the machine-readable medium 226 caninclude multiple media (e.g., a centralized/distributed database and/orassociated caches and servers) that store one or more sets ofinstructions 228. The machine-readable (storage) medium 226 can includeany medium that can store, encoding, or carrying a set of instructionsfor execution by the computing system 200. The machine-readable medium226 can be non-transitory or comprise a non-transitory device. In thiscontext, a non-transitory storage medium can include a device that istangible, meaning that the device has a concrete physical form, althoughthe device can change its physical state. Thus, for example,non-transitory refers to a device remaining tangible despite this changein state.

Although implementations have been described in the context of fullyfunctioning computing devices, the various examples are capable of beingdistributed as a program product in a variety of forms. Examples ofmachine-readable storage media, machine-readable media, orcomputer-readable media include recordable-type media such as volatileand non-volatile memory devices 210, removable flash memory, hard diskdrives, optical disks, and transmission-type media such as digital andanalog communication links.

In general, the routines executed to implement examples herein can beimplemented as part of an operating system or a specific application,component, program, object, module, or sequence of instructions(collectively referred to as “computer programs”). The computer programstypically comprise one or more instructions (e.g., instructions 204,208, 228) set at various times in various memory and storage devices incomputing device(s). When read and executed by the processor 202, theinstruction(s) cause the computing system 200 to perform operations toexecute elements involving the various aspects of the disclosure.

Overview of Automated Coverage Bin Analysis

FIG. 3 is a flowchart 300 that illustrates an automated process foridentifying cells requiring coverage and/or capacity adjustment. Atblock 310, the coverage analysis tool (which includes an automatedcoverage bin data analysis algorithm described here) receives cellularnetwork traffic information (e.g., from a pre-existing database). Insome implementations, the cellular network traffic information includesgeo-located call information or data traffic information correspondingto one or more radio access technologies (RATs). For example, thecellular network traffic information can include Evolved UniversalMobile Telecommunications System Terrestrial Radio Access Network(EUTRAN) New Radio (NR) dual connectivity (EN-DC) cellular networktraffic information based on a non-standalone (NSA) New Radio (NR) RAT.

The non-standalone mode of 5G NR, uses a 4G Long Term Evolution (LTE)control plane and 5G NR user plane which allows cellular networkoperators to speed up the deployment of 5G NR on top of the operators'existing 4G LTE infrastructure. Because of the ongoing development ofthe 5G NR network, 5G NR data sources can be limited, and call datamight not be readily available from existing datasets (e.g., TruecallLSR data). Furthermore, unlike in LTE networks containing neighborinformation, calculation of distance to 5G NR serving cell neighbors canbe complicated by absence of neighbor information in NSA 5G NR datasets.Moreover, neighbor 5G NR sites are constantly being upgraded astechnology evolves and new sites being added increasing the probabilityof coverage holes being introduced and necessitating the need torecursively optimize coverage via the disclosed automated coverage binanalysis tool. The automated coverage analysis tool includes analgorithm that analyzes geo-located user call data to assess cellcoverage and provide recommendations to correct coverage issues. Use ofthe disclosed technology precludes the use of time/resource intensiveand error prone conventional manual coverage analysis techniques. Asdescribed below, the coverage analysis tool scrapes 5G information fromcalls to identify coverage tuning opportunities for 5G cells (e.g.,automated coverage optimization). This drive-less coverage tuning of the5G network saves hours, days or weeks of drive test data collection andprovides a quicker network optimization when compared to conventionalmethods. Although the disclosed systems and methods use 5G NR NSA RATswith EN-DC mode as representative data source, the systems and methodsare applicable to different RATs and operation modes includingstandalone (SA) NR with or without carrier aggregation (CA) or dualconnectivity (DC). It will also be appreciated that, although describedin relation to improving coverage, the same techniques described herecan be used to improve capacity in different spatial regions of thewireless communication network.

At block 320, the coverage analysis tool determines (e.g., extracts)call information (e.g., information related to one or more calls or datatraffic) corresponding to a particular RAT from the cellular networktraffic information (e.g., extracts 5G call information from thecellular network traffic information).

For example, as shown in Table 500 in FIG. 5 which illustratesrepresentative cellular traffic information for automated coverageanalysis, the cellular network traffic information can includeinformation stored in a database on a periodic basis related to 4G LTEnetwork traffic only (e.g., row 510 in FIG. 5 ), and information relatedto both 4G LTE and 5G NR network traffic (e.g., row 520 in FIG. 5 ). Forexample, Row 520 in FIG. 5 might correspond to Non-standalone (NSA) 5Ginformation with a 4G LTE anchor. The coverage analysis tool extractsall the calls with 5G information such as rows 520 and 580 from adatabase, table, or other storage containing all the call information.The coverage analysis tool further filters and organizes the extractedcall data to get 5G cell and radio frequency (RF) information relevantfor automated coverage analysis including, for example, the 5G NR signalstrength (e.g., reference signal received power (RSRP) value 528), thesignal quality (e.g., reference signal received quality (RSRQ) value529), and the physical cell identifier (PCI) (e.g., the PCI value 525).

The different columns in Table 500 in FIG. 5 can be used for differentpurposes in the coverage analysis tool. For example, the5G_nr_Serving_Cell column 575 can be used to map to easier networkcell_name (e.g., a 14 digit unique number can be reversed mapped to analphabetical name for easier identification such as “LBQ06091C11”)allowing column 575 to be used to get column 570.

The 5G_nr_serving_pci column 576 can be used to filter the network celllist, so that the distance from the extracted call to the cells iscomputed efficiently. Instead of finding the distance of a call from allthe cells in network, physical cell identifier (PCI) information incolumn 576 can be used to filter potential target cells so that onlycells with PCI identified in call is used in the distance computation.This can save time in the coverage analysis tool's calculations, e.g.,when millions of calls are analyzed. Mapping serving cells togeo-located call information using PCI information is described in moredetail below with respect to FIG. 4 .

The extracted call information is a collection of calls from all layersof 5G network. Each layer has a unique absolute radio frequency channelnumber (ARFCN) value as indicated in the 5G_nr_serving_ARFCN column 577.To accurately determine cells where the calls were made and distances,ARFCN information can be used to filter the target cells. For example,distance between call and cell can be calculated only on cellstransmitting on the specific ARFCN. Also, for cell-to-cell distancecalculation (e.g., for “first tier” distance calculation), only cells ofthe same ARFCN are used. Calculating the first tier distance isdescribed in more detail below in relation to block 340 of FIG. 3 andFIG. 6 .

The 5G_nr_rsrp column 578 and 5G_nr_rsrq column 579 can be used todetermine how weak or strong the coverage was when the call was made.The RSRP and RSRQ values in these columns help identify over-shooter andunder-shooter cells. For example, the coverage check can help identifyover-shooter/under-shooter cells from among potential over-shooter andpotential under-shooter cells. Additional details on determiningunder-shooter and over-shooter cells based on signal strength or signalquality can be found below with respect to FIG. 10 .

Turning back to FIG. 3 , at block 330, the coverage analysis tooldetermines from the extracted call information (e.g., the extracted 5GNR information), a serving cell for each extracted call. For example,the coverage analysis tool determines a 5G serving cell that is likelyserving each 5G call in the extracted 5G call information. Additionaldetails on a representative method that the coverage analysis tool canuse to determine the 5G serving cells for each of the 5G calls isdescribed below in relation to FIG. 4 .

At block 340, the coverage analysis tool computes a distance from eachserving cell to one or more neighbor cells (e.g., a “first tier”distance from each 5G serving cell to its closest neighbor cell withincoverage). The first tier distance can be used as a visual aid bynetwork engineers to limit coverage from the cell to be optimized.Additional details on a representative method that the coverage analysistool can use to compute the distance from the serving cell to the one ormore neighbor cells is described below in relation to FIG. 6 . As willbe described in FIG. 6 , calculating the first tier distance accuratelyensures accurate results from the automated coverage analysis tool.

At block 350, the coverage analysis tool determines a first coverage andsecond coverage for each of the serving cells. The first coverage isbased on the distance computed in block 340 between the serving cell andthe one or more neighbor cells (e.g., based on the first tier distance).The second coverage is based on the distance between the serving celland a geographic location for each of the extracted geo-located 5G calls(e.g., distance from the serving cell to the geographic location wherethe mobile communication device was located when the call was made orreceived).

In some implementations, the coverage analysis tool uses the first tierdistance calculated for each sector to assess calculated coverage vsexpected coverage for the cell. The expected coverage is the originaldesigned coverage of the cell. When a cell is initially designed,coverage can be defined based on signal strength (RSRP) above a certaindesign threshold (e.g., −90 dBm) at the first tier distance. Suchcoverage threshold can vary in different environments (e.g., urban areasvs rural areas) and also depending on how dense the buildings are (e.g.,Manhattan can have a design threshold of −65 dBm but Nassau county inLong Island can have a design threshold of −85 dBm because there ishigher penetration loss due to buildings). The antenna tilt, radiosignal power, and other network parameters can be set based on height ofthe cell and intended coverage area (among other factors). Conversely,the calculated coverage is an estimate of cell coverage based on thecoverage data (RSRP/RSRQ) from the extracted call. The calculatedcoverage is the actual coverage as seen by network subscribers. If thecalculated coverage differs significantly from design coverage, furthercoverage tuning is required such as adjusting the radio signal power orantenna tilt.

The distance between the serving cell and the geo-located call data canbe determined based on the latitude and longitude coordinatescorresponding to the call data (e.g., latitude 522 and a longitude 523in FIG. 5 ) and a geographic location of the 5G serving cell (e.g., 5Gserving cell 524 in FIG. 5 ) (latitude and longitude of 5G serving cell524 not shown in FIG. 5 ).

Coverage of a cell depends on radio frequency (RF) signal propagationparameters including the antenna type in the cell (e.g., the gain,beamwidth, polarization, etc., of a sector antenna of the serving cell)and the radio propagation properties of the radio channel which is basedon, for example, the frequency, path loss, multipath interference, etc.A cell provides coverage to mobile devices or user equipment (UEs) inthe cellular network when the cell is the “strongest” among other cellsin the area. If the cell is not the strongest in the area but is stilltransmitting signals to a particular UE in a particular geographic spot,that cell can act as an interferer and thereby degrade the RSRQ at theUE.

At block 360, the coverage analysis tool determines whether to identifythe serving cell for a coverage corrective action based on a comparisonbetween the first coverage and the second coverage. In someimplementations, the determination or recommendation on whether toidentify the serving cell as needing a coverage corrective action isalso based on whether a signal strength (e.g., RSRP) and/or a signalquality (e.g., RSRQ) of the calls served by the serving cell is above orbelow a signal strength or signal quality threshold. The flagged cells(serving cells identified for corrective action) can be reported invarious ways including on a spreadsheet report of flagged cells or viadifferent visual rendering of problem cells in a network coverage map.

In some implementations, the report of cells flagged for correctiveaction (or the visual rendering of such cells in a network coverage map)can include a ranking of cells from worst-offenders to least offenders.For example, this ranking can be based on the deviation between theexpected coverage and the calculated coverage, or as will be describedin relation to FIG. 10 , based on the deviation between the distancefrom the serving cell to one or more neighbor cells (first tierdistance) and the distance from the serving cell to each call served bythe serving cell. The most critical cells (e.g., cells that networkengineers should attend to first) can be first in the list or include apriority indicator or a different visual rendering (e.g., dark red).

At block 370, in some implementations, the coverage analysis tool alsodetermines the type of coverage corrective action to recommend. Forexample, after the coverage analysis tool identifies coverage“offenders” at block 360 by filtering “outliers,” the coverage analysistool can recommend to the network engineering or user of the coverageanalysis tool to adjust the tilt (elevation) of the serving cell antennaor adjust the transmit power to adjust coverage for the offender cells.For example, down tilting an elevation of a sector antenna of theserving cell or reducing the transmit power can reduce the number ofovershooting calls and uptilting an elevation of the sector antenna canreduce the number of undershooting calls. Over-shooter cells serve areasthat the cells were not designed to serve which can lead to droppedcalls and/or interference. Consequently, reducing the number of cellscausing overshoot in RF coverage can improve the network's performanceand quality of the user experience. Reducing under-shooters improves RFcoverage allowing the operator to serve more users.

The coverage analysis tool can also recommend and approximate value forthe antenna tilt (down tilt or up tilt) or an approximate value of poweradjustment (power reduction or increase) recommended based on, forexample, the height of the serving cell antenna, height and distance ofadjacent buildings or other tall structures in the vicinity of theserving cell, the intended distance to extend coverage to or from, thefrequency band, antenna properties (gain, beamwidth, front-to-backratio, etc.), transmit power, etc. The network engineer can apply therecommended tilt or power adjustment, rerun the coverage analysis tool,and adjust again by a certain amount (e.g., by a certain degree of tiltor certain dBm or Watts of power adjustment) again until they obtain thedesired coverage results.

In some implementations, the network can automatically adjust a propertyof the over-shooter/under-shooter serving cell to adjust a coverage or acapacity of the serving cell based on the results of the coverageanalysis. For example, the coverage analysis tool can cause a node inthe cellular/wireless communication network to automatically adjust theantenna tilt of a sector antenna via electrical up- or down-tilt orincrease or decrease the transmit power of the serving cell based on thetype and extent of coverage issue (e.g., whether the cell isovershooting or undershooting and the extent ofovershooting/undershooting).

In some implementations, the coverage analysis tool can be coupled to anelectrical tilt capability of the antenna and can repeatedly adjust theproperty of the serving cell (e.g., repeatedly up tilt/down tilt orincrease/decrease power) and rerun analysis until the coverage issue isresolved (e.g., until the designed coverage matches the actualcoverage). For example, as part of a self-optimizing orself-organization network (SON) capability, the coverage analysis toolcan repeatedly apply, or cause to be applied, electrical down tilt or uptilt in certain increments (or automatically cause to increase ordecrease transmit power) to a cell sector antenna when the number ofover-shooter or under-shooter calls served by the cell is above apredetermined threshold, and continue to apply tilt or power adjustmentsover time until the number of over-shooter/under-shooter calls fallsbelow the predetermined threshold. For example, the coverage analysistool and/or the SON network can continue to apply the corrective action,or can select the degree of up- or down-tilt or amount of powerincrease/decrease, until the coverage analysis tool determines (e.g.,from subsequent analysis as described above) that the intended,designed, or expected coverage of the serving cell matches the actual orcomputed coverage. Automatic adjustment of tilt or transmit power can bedone with or without manual intervention by a user. For example, in someimplementations, the results of the coverage analysis can initiate theautomatic tilt or power adjustment in the network. In otherimplementations, a user can instruct only certain sector antennas orcells to automatically adjust tilt or power level based on the resultsof the coverage analysis and/or set limits to the automated adjustments.

In some implementations, the coverage analysis tool and/or the SONnetwork can determine the order of cells to apply the corrective actionbased on the severity of the cell's coverage problem as described below(e.g., based on a priority indicator indicating the severity of theproblem as described below, the coverage analysis tool and/or the SONnetwork can determine to apply a corrective action to a more problematicserving cell before applying a corrective action to a less problematicserving cell).

Mapping Serving Cells to Geo-Located Call Data

FIG. 4 is a flowchart 400 that illustrates mapping serving cells togeo-located call information (e.g., reverse mapping of 5G cells to the5G call information extracted at block 320 in FIG. 3 ). At block 410,the coverage analysis tool determines a primary cell identity orphysical cell identifier (PCI) value associated with a call in theextracted 5G call information. For example, as shown in the cellulartraffic information table 500 in FIG. 5 , the coverage analysis tool canextract row 520 call data information and determine that the servingcell for that call is identified with PCI value label 525 (PCIvalue=130).

At block 420, the coverage analysis tool determines one or more cells inthe cellular network corresponding to or identified by the PCIdetermined at block 410. For example, 5G NR specifies up to 1008 uniquePCI values and a value can be reused in the network so the coverageanalysis tool determines a location of all the cells that reuse the PCIvalue.

At block 430, the coverage analysis tool computes a distance from eachof the cells identified at block 420 to the location of the 5G call inthe extracted 5G call data. In some implementations, the coverageanalysis tool includes information from a network information databaseor table which contains the geographic location (e.g.,latitude/longitude) of each cell in the network, the azimuth of the cell(or azimuth of different sector antennas in the cell), and the PCI valueidentifying the cell. Additionally, the extracted 5G geolocated calldata includes a spatial/geographic location associated with the call,e.g., latitude 522 and longitude 523 in extracted call data row 520 inFIG. 5 . Using the location of the cells with the given PCI and thelocations of the calls with the same PCI, the coverage analysis tool cancompute the distance from each of those cells to each call. As will bedescribed in additional detail below, once the distance is calculatedfor every call in the geolocated call information table (each havingspecific PCI), to all cells in the network with the same PCI, theserving cell is chosen based on, for example, shortest distance andorientation.

At block 440, the coverage analysis tool determines based on thedistance computed at block 430, and based on an orientation of all thecells, the closest cell having the given PCI value to the callassociated with the same PCI value. For example, the coverage analysistool can determine which cells with a PCI value of 130 have sectorantennas with an azimuth or angle of transmission in the direction ofthe call(s) served by a cell with a PCI value of 130. The coverageanalysis tool can then determine which cell, of all the cells pointingin the direction of the corresponding call, has the shortest distance tothe call. This closest cell is the most likely cell serving the call andis thus identified as the serving cell for the call, for example, asdescribed in relation to block 330 in FIG. 3 . In some implementations,the closest cell information is appended to a table containing thegeolocated call information and the table is then sorted by cell forsubsequent analysis by the coverage analysis tool.

Determining Distance from Serving Cell to Eligible Neighbor Cells

FIG. 6 is a flowchart 600 that illustrates determining a distancebetween a serving cell and one or more neighbor cells that are relevantfor automated coverage analysis. At block 610, the coverage analysistool determines an angle of transmission or azimuth and a geographiclocation (e.g., lat/lon coordinates) or each cell (or each sectorantenna in each cell) in the cellular network.

At block 620, the coverage analysis tool computes or determines adistance from each cell to every other cell in the cellular network (orfrom each sector antenna to every other sector antenna in the network)based on the geographic locations of each cell/sector determined atblock 610.

At block 630, the coverage analysis tool determines or isolates a firstnumber of cells closest to a source serving cell (e.g., the closest Ncells to the serving cell, where the serving cell is determined at block330 in FIG. 3 or determined by Flow 400 in FIG. 4 ). In someimplementations, the coverage analysis tool can use the distancescomputed at block 620 to determine the closest cells. In otherimplementations, the closest cells to each cell are predetermined andstored in a database or other storage for lookup by the coverageanalysis tool.

At block 640, the coverage analysis tool determines an orientation orbearing of the serving cell relative to each of the cells in the closestN cells determined at block 630.

At block 650, using the orientation or the bearing of the serving celldetermined at block 640, and the angles of transmission or azimuth ofeach of the cells or each sector of each cell in the closest N cellsdetermined at block 610, the coverage analysis tool determines which ofthe N closest cells are eligible neighbor cells. For example, thecoverage analysis tool determines one or more neighbor cells indirection of coverage of the source serving cell and uses these neighborcells for subsequent coverage analysis as described further below. Thevalue of the number of the closest cells selected (N) can be chosen bythe user of the coverage analysis tool or by the network based on thenetwork topology, e.g., cell density of the wireless network (number ofcells per square area). For example, N can be large (e.g., N=6) forurban areas or areas with dense cells (e.g., 5G NR small cells), andsmall (e.g., N=3) for rural areas where there might not be 6 neighborcells to consider for optimization.

In some implementations, the coverage analysis tool can determinewhether the one or more neighbor cells are in a direction of coverage ofthe serving cells by determining whether the coverage of the servingcell (based on the azimuth and beamwidth or angle of transmission of aserving cell sector antenna) overlaps (fully or partially) the coverageof the neighbor cell (based on an azimuth and beamwidth or angle oftransmission of a neighbor cell sector antenna). Antenna azimuth andbeamwidth along with distance between serving cell and neighbor cell areused to determine whether they serve in same direction.

At block 660, the coverage analysis tool determines if any of theneighbor cells determined at block 650 is in a direct angle oftransmission. For example, turning to map 800 in FIG. 8 whichillustrates a cellular network with a source serving cell aligned at adirect angle of transmission to a single neighbor cell, the coverageanalysis tool can determine at block 660 that serving cell 810 (or asector antenna in serving cell 810) is in a direct angle of transmissionto cell 830 (or a sector antenna in cell 830). Conversely, turning tomap 900 in FIG. 9 which illustrates a cellular network with a sourceserving cell not aligned in a direct angle of transmission to a singleneighbor cell, the coverage analysis tool can determine at block 660that serving cell 910 is not in a direct angle of transmission to cells920 and 930.

At block 662, if there is a cell in the neighbor cells list at a directangle of transmission, the coverage analysis tool computes the distancefrom the serving cell to the closest neighbor cell in a direct angle oftransmission (e.g., the “first tier” distance). For example, thecoverage analysis tool can use the distances computed at block 620.

Conversely, at block 664 if there is no cell in the neighbor cells at adirect angle of transmission, the coverage analysis tool computes anaverage distance from the source serving cell to the closest neighborcells in a direction of transmission within the serving cell's antennabeamwidth.

In some implementations, the average distance or first tier distancefrom the serving cell to the closest neighbor cells can be based oncomputing the sum of the distances from the serving cell to eachneighbor cell divided by the number of neighbor cells (e.g., a simpleaverage of the distances). In other implementations, an arc or line canbe defined (e.g., arc 950 in FIG. 9 ) between the eligible neighborcells and a distance between the serving cell and the arc/line midpointcan be computed to determine the first tier distance. If the first tierdistance is too small, the coverage analysis tool could find too manyover-shooters (too many false positives) which could happen if thecoverage analysis tool determines the first tier distance withoutaveraging (e.g., by taking the absolute distance to the closest site toany sector without taking directionality into consideration).

In some implementations, the coverage analysis tool can determine thefirst tier distance using handover statistics. For example, based onhandover statistics from key process indicators (KPI) between sourcesector of the serving cell and sectors of the neighbor cells, thecoverage analysis tool can sort the neighbors from highest to lowestbased on handover counts and then average the distance between the top Nneighbors with highest handovers (or the neighbors with number ofhandover or handover attempts above a threshold number). In someimplementations, the coverage analysis tool can determine the top Nneighbors based on the top X percentile of handover counts or based onabsolute counts. For example, all the neighbors with a minimum of 100handovers or handover attempts between source and target or all theneighbors with more than X % of all handover attempts/counts.

Determining Eligible Neighbor Cells

FIG. 7 is a flowchart 700 that illustrates determining relevant oreligible neighbor cells in a search area based on a source servingcell's antenna azimuth and beamwidth. At block 710, the coverageanalysis tool determines an azimuth and a beamwidth of an antenna (e.g.,a sector antenna) of the source serving cell.

At block 720, the coverage analysis tool determines the N cells closestto the source serving cell, for example, as described in relation toblock 630 in FIG. 6 .

At block 730, the coverage analysis tool determines a search area aroundthe azimuth direction of the source serving cell's sector antenna. Insome implementations, the coverage analysis tool determines +/−D offsetdegrees above and below the azimuth direction (e.g., +/−10° from North,if the azimuth direction or bearing is due North).

At block 740, the coverage analysis tool determines if there is aneighbor cell in the search area determined at block 730. For example,turning to map 800 in FIG. 8 , the coverage analysis tool can determineat block 730 a search area 816 by taking +D° (angle 811) and −D° (angle813) from azimuth direction 812. At block 740, the coverage analysistool can determine that there is a neighbor cell 830 within the searcharea 816.

If there is one or more neighbor cells within the search area, thecoverage analysis tool at block 742 adds the neighbor cell(s) found to alist of eligible neighbor cells (e.g., neighbor cells that could be usedas a basis for finding the first tier distance like described inrelation to flow 600 in FIG. 6 ). For example, the list of eligibleneighbor cells are the one or more neighbor cells in a direction ofcoverage of the serving cell determined at block 650 in FIG. 6 .

If at block 740 there is no neighbor cell with the search area, thecoverage analysis tool at block 744 expands the search area by anadditional +/−D offset degrees (e.g., a new search area of +/−20° fromNorth, where the azimuth direction or bearing is due North). Thecoverage analysis tool then determines at block 740 if there is aneligible neighbor cell in the expanded search area and, if not, furtherexpands the search area by the +/−offset degrees until the search areacovers an area defined by an angle equal to the beamwidth of the servingcell sector antenna (e.g., until search area is defined by an angleequal to 120° for a 120° beamwidth serving cell sector antenna). Forexample, turning to map 900 in FIG. 9 , the coverage analysis tool canfind eligible cells 920 and 930 within expanded search area 916 wherethe search area 916 has been expanded to encompass an angle equal to theserving cell antenna's beamwidth 915.

If at block 744 the search area is equal to the beamwidth and no cellshave been identified in the search area for the first tier distancecalculation (e.g., list of eligible neighbor cells at block 742 isempty), a default inter-site distance can be used as a constantreference value (e.g., 1 km). This reference value can be used as thefirst tier for any cell where neighbor cells do not exist such assectors or cells next to beaches where the sectors pointing towards theocean may not have neighbors.

At block 750, the coverage analysis tool determines an average distancefrom the source serving cell to one or more closest neighbor cells ofthe eligible neighbor cells added to the list of eligible neighbor cellsat block 742. For example, the coverage analysis tool determines thisaverage distance as described in relation to blocks 650, 660, 662, and664 in FIG. 6 .

Identifying Problem Cells

FIG. 10 is a flowchart 1000 that illustrates identifying serving cellswith over-shooter or under-shooter calls. At block 1010, the coverageanalysis tool computes or determines a first distance from the sourceserving cell to one or more neighbor cells, e.g., a first tier distanceas determined in block 340 of FIG. 3 .

In some implementations, the coverage analysis tool can determine asecond tier distance (e.g., as described in relation to FIG. 6 but basedon the next closest neighbor cells in direction of coverage). Thecoverage analysis tool can use the second tier distance to identifyseverely overshooting cells.

At block 1020, the coverage analysis tool determines or computes asecond distance from the serving cell to the geographic location of eachcall served by the serving cell (e.g., geographic location from theserving cell to the location of the wireless communication deviceassociated with the call). For example, once the coverage analysis tooldetermines the serving cell serving each call based on the PCIs of thecells in the network and PCIs of the calls as described in relation toflow 400 in FIG. 4 , the coverage analysis tool can determine thedistance between the serving cells and the corresponding calls served bythe serving cell at block 1020.

At block 1030, the coverage analysis tool compares the first distanceand second distance to determine if there are any calls beyond the firsttier distance (e.g., where the second distance is greater than the firstdistance).

At block 1032, the coverage analysis tool determines the number of callsabove the first tier distance and with a signal strength above a firstsignal strength threshold (e.g., −90 dBm). The calls beyond the firstdistance (e.g., the first tier distance) and with strong signals (signalstrength above a threshold) are over-shooter calls.

At block 1034, the coverage analysis tool determines the number of callslocated within a certain percentage (e.g., x %) of the first distance(e.g., all calls served by a certain cell and contained within 50% ofthe first tier distance) and with signal strength below a second signalstrength threshold (the first signal strength threshold for determiningover-shooter cells and the second signal strength threshold fordetermining under-shooter cells can be the same or different). Thesecalls indicate that the cell serving the calls is an under-shooter cell.

At block 1040, the coverage analysis tool determines serving cellsrequiring remedial action to fix over-shooter/under-shooter coverageissues by considering the number of over-shooter calls per cell at block1032 or the number of under-shooter calls per cell at block 1034. Forexample, the coverage analysis tool can determine whether the number ofcalls with signal strength above the first threshold when the seconddistance is greater than the first distance (beyond first tier distance)is above a first threshold number of calls. Similarly, the coverageanalysis tool can determine whether the number of calls with signalstrength below the second threshold when the second distance is lessthan the first distance (within a certain percentage of first tierdistance) is above a second threshold number of calls. This way, thecoverage analysis tool can ignore few outlier calls and recommendcorrective action when the number of problem calls is sufficiently largeto point to a problem with the serving cell configuration or settings.

In some implementations, the number of bins/cells or calls/cellovershooting or undershooting is based on the dataset or the number ofcells in the network. For example, the first and second threshold numberof calls can be selected to control the number of cells identified forcorrective action (e.g., limit the number of cells per run identifiedfor correction). For example, the thresholds can be selected so no morethan X cells out of Y total cells in the network are identified forcorrective action. In some implementations, all offending cells areidentified and the X most offending cells are reported for correction.

In some implementations, first distance computed at block 1010 and thesecond distance computed at block 1020 can be used to determine thedegree of antenna up-tilt or down-tilt or the amount of power increaseor decrease. For example, for a first cell where the over-shooting callsare further away from the first tier distance than the over-shootingcalls of a second cell are, the first cell could have a higher degree ofantenna down-tilt (relative to an initial tilt) than the second cell; orthe first cell could get a larger power decrease than the second cell.Similarly, if the number of under-shooting calls are clustered muchcloser to a first serving cell than under-shooting calls are clusteredto a second serving cell, the first serving cell could require a largerantenna up-tilt or a larger power increase than the second serving cell.

For example, the coverage analysis tool can determine at block 1040 thata source serving cell is problematic when a certain percentage of callsof the total number of calls in the dataset are under-shooter orover-shooter calls (e.g., if use a 10% threshold, and there are 100calls in the network, if 10 calls associated with a cell areover-shooter calls, that cell would be identified for coverageimprovement such as down tilt or power reduction).

In some implementations, the coverage analysis tool can automaticallydetermine this percentage threshold as part of a recursive optimizationalgorithm such as a machine learning algorithm. A lower percentagethreshold will yield more false positives and a higher percentagethreshold will limit the number of over-shooters identified. In amanually optimized network, the targeted list of over-shooters candepend on how aggressive the network engineers or other users of thecoverage analysis tool want to be and the resources available formanually tuning coverage and capacity. In an automated system, thepercentage threshold can be selected to be high enough to minimize thenumber of false positives.

In some implementations, the coverage analysis tool can also indicatethe extent of the problem for problematic cells which can give networkengineers or self-optimizing networks an indication of what cells toadjust first. For example, the coverage analysis tool can generate areport of cells flagged for corrective action with a priority indicatorbased on the number of over-shooter/under-shooter calls associated withthe serving cell or extent of over-shooting/under-shooting associatedwith the serving cell.

In some implementations, the priority indicator can be based on theextent to which a first distance representing the distance from theserving cell to one or more neighbor cells differs from a seconddistance representing the distance from the serving cell to thegeographic locations of the calls (e.g., the geographic locations of themobile devices that placed or received the calls being analyzed). Forexample, a priority indicator indicating a higher priority can be usedwhen the second distance is much larger than the first distance (e.g.,when the degree of overshoot is very large) or when the second distanceis much smaller than the first distance (e.g., the actual coverage ismuch smaller than the designed coverage).

In some implementations, the priority indicator can be based on thenumber of over-shooter or under-shooter calls per cell. For example, aserving cell with a higher number of overshooting or undershooting callswould have a priority indicator indicating a higher priority than aserving cell with a smaller number of over-shooting or under-shootingcalls.

In some implementations, the coverage analysis tool can overlay adifferent visual treatment in a visual rendering of a network coveragemap based on the priority indicator such that the visual treatmentindicates the most problematic cells (e.g., bright red for cells withthe largest number of over-shooter calls or furthest over-shooters andgreen for cells without any recommended coverage corrective action).

In some implementations, the prioritization of cells for correctiveaction as described above can be used to direct the priority of cellsfor self-optimization in a self-optimizing network (SON). For example,the coverage analysis tool can apply electrical down tilt to a servingcell serving the most over-shooter calls first before applyingelectrical down tilt on serving cells serving fewer over-shooter calls.

For example, turning to map 1100 in FIG. 11 which illustrates a cellularnetwork with over-shooter calls, the coverage analysis tool at block1040 can determine that source serving cell 1110 serves too manyovershooting calls as seen in region 1115 which is beyond the arc 1150which defines the first tier distance. Because the serving cell 1110 isserving calls in region 1115 which is beyond the design coverage area1112, serving cell 1110 is an over-shooter cell. The coverage analysistool can flag serving cell 1110 as a potential source of interference tocells also serving calls in region 1115. The coverage analysis tool canrecommend serving cell 1110 for down tilt or power reduction asdescribed above in relation to block 370 in FIG. 3 . Once the networkengineer has applied the recommended down tilt to the serving cell'santenna (or the coverage analysis tool has applied or caused to beapplied an electrical down tilt), the automated coverage analysis isrepeated to verify if there are additional over-shooter calls. Theprocess is repeated until the network's coverage is optimized (e.g., theintended or designed coverage area matches the actual or computedcoverage area).

Turning to map 1200 in FIG. 12 which illustrates a cellular network withunder-shooter calls, the coverage analysis tool at block 1040 candetermine that source serving cell 1210 serves too many undershootingcalls as seen in region 1215 which is contained within 50% of the firsttier distance depicted by arc 1250. The coverage analysis tool canidentify serving cell 1210 as a good candidate for up tilting orcoverage expansion (e.g., increasing transmit power) because it iscurrently serving a high percentage of under-shooter calls relative tothe total number of calls in the network and the coverage in the area isweak (e.g., weak coverage in the design area 1212 including in region1215 containing under-shooter calls).

In some implementations, the coverage analysis tool can use TrueCall LSRdata and be based on Python programming language. It will beappreciated, however, that the coverage analysis tool is independent onthe source of call data or cellular network traffic information; isindependent on the radio access technology (RAT), whether non-standalone(NSA) NR, standalone (SA) NR, EN-DC, LTE, UMTS, etc.; and, isindependent on the frequency band that the serving cell is configured tooperate on (e.g., low band like band n71 at 600 MHz, midband like bandn41 at 2.5 GHz, or mmWave like band n260 at 39 GHz).

In some implementations, the coverage analysis tool at block 1040 canuse additional criteria to determine over-shooter/under-shooter callsincluding the quality of the signal (e.g., RSRQ worse than −16), roamingor switching from NR to LTE which is an indication of a bad call qualityin an NSA NR RAT, etc.

In addition to under-shooter/over-shooter optimization, the coverageanalysis tool, with advanced analysis, can be used to identify areaswhere additional network elements need to be added for coverageenhancement (e.g., new sites, small cell deployments, etc.). In someimplementations where vertical or elevation location data is available(e.g., smartphone barometer based elevation detection), the coverageanalysis tool can assess if coverage in higher floors of buildings in anarea is lacking and the cell can be tuned to cover the higher floors.For example, the coverage analysis tool can recommend an antenna up-tilt(or the network can automatically apply an electric up-tilt) where theserving cells is found to be serving lower floors but not higher floorsas designed (better coverage in lower elevations). Conversely, thecoverage analysis tool can recommend or cause to be applied an antennadown-tilt if the serving cell is serving higher floors but not lowerfloors (better coverage in higher elevations than in lower elevations,e.g., coverage in higher elevations meets a coverage goal but coveragein lower elevations does not meet a coverage goal where coverage goalcan be RSRP, RSRQ, number of dropped calls, etc.).

In some implementations, the coverage in lower and higher elevations canbe determined based on the computed first tier distance, the distancefrom the serving cell to the mobile device when the mobile device is onthe ground, the elevation location data of the mobile device, and thesignal strength of the mobile device. For example, if a mobile device onthe ground floor is beyond the first tier distance but the signalstrength is below a signal strength threshold, but a mobile device onthe same latitude/longitude but on a higher floor has a signal strengthabove a signal strength threshold, this could indicate a need tooptimize coverage in the higher floors (e.g., by down-tilting the sectorantenna to reduce the higher-floor over-shooters).

REMARKS

The terms “example”, “embodiment” and “implementation” are usedinterchangeably. For example, reference to “one example” or “an example”in the disclosure can be, but not necessarily are, references to thesame implementation; and, such references mean at least one of theimplementations. The appearances of the phrase “in one example” are notnecessarily all referring to the same example, nor are separate oralternative examples mutually exclusive of other examples. A feature,structure, or characteristic described in connection with an example canbe included in another example of the disclosure. Moreover, variousfeatures are described which can be exhibited by some examples and notby others. Similarly, various requirements are described which can berequirements for some examples but no other examples.

The terminology used herein should be interpreted in its broadestreasonable manner, even though it is being used in conjunction withcertain specific examples of the invention. The terms used in thedisclosure generally have their ordinary meanings in the relevanttechnical art, within the context of the disclosure, and in the specificcontext where each term is used. A recital of alternative language orsynonyms does not exclude the use of other synonyms. Specialsignificance should not be placed upon whether or not a term iselaborated or discussed herein. The use of highlighting has no influenceon the scope and meaning of a term. Further, it will be appreciated thatthe same thing can be said in more than one way.

Unless the context clearly requires otherwise, throughout thedescription and the claims, the words “comprise,” “comprising,” and thelike are to be construed in an inclusive sense, as opposed to anexclusive or exhaustive sense; that is to say, in the sense of“including, but not limited to.” As used herein, the terms “connected,”“coupled,” or any variant thereof means any connection or coupling,either direct or indirect, between two or more elements; the coupling orconnection between the elements can be physical, logical, or acombination thereof. Additionally, the words “herein,” “above,” “below,”and words of similar import can refer to this application as a whole andnot to any particular portions of this application. Where contextpermits, words in the above Detailed Description using the singular orplural number may also include the plural or singular numberrespectively. The word “or” in reference to a list of two or more itemscovers all of the following interpretations of the word: any of theitems in the list, all of the items in the list, and any combination ofthe items in the list. The term “module” refers broadly to softwarecomponents, firmware components, and/or hardware components.

While specific examples of technology are described above forillustrative purposes, various equivalent modifications are possiblewithin the scope of the invention, as those skilled in the relevant artwill recognize. For example, while processes or blocks are presented ina given order, alternative implementations can perform routines havingsteps, or employ systems having blocks, in a different order, and someprocesses or blocks may be deleted, moved, added, subdivided, combined,and/or modified to provide alternative or sub-combinations. Each ofthese processes or blocks can be implemented in a variety of differentways. Also, while processes or blocks are at times shown as beingperformed in series, these processes or blocks can instead be performedor implemented in parallel, or can be performed at different times.Further, any specific numbers noted herein are only examples such thatalternative implementations can employ differing values or ranges.

Details of the disclosed implementations can vary considerably inspecific implementations while still being encompassed by the disclosedteachings. As noted above, particular terminology used when describingfeatures or aspects of the invention should not be taken to imply thatthe terminology is being redefined herein to be restricted to anyspecific characteristics, features, or aspects of the invention withwhich that terminology is associated. In general, the terms used in thefollowing claims should not be construed to limit the invention to thespecific examples disclosed herein, unless the above DetailedDescription explicitly defines such terms. Accordingly, the actual scopeof the invention encompasses not only the disclosed examples, but alsoall equivalent ways of practicing or implementing the invention underthe claims. Some alternative implementations can include additionalelements to those implementations described above or include fewerelements.

Any patents and applications and other references noted above, any thatmay be listed in accompanying filing papers, and the assignee'sconcurrently filed U.S. patent application Ser. Nos. 11/469,259 and17/469,462 respectively entitled COVERAGE IMPROVEMENT FOR 5G NEW RADIOWIRELESS COMMUNICATION NETWORK and COVERAGE IMPROVEMENT FOR 5G NEW RADIOWIRELESS COMMUNICATION NETWORK TO AUTOMATICALLY ADJUST CELL PROPERTIESTO IMPROVE COVERAGE AND CAPACITY, are incorporated herein by referencein their entireties, except for any subject matter disclaimers ordisavowals, and except to the extent that the incorporated material isinconsistent with the express disclosure herein, in which case thelanguage in this disclosure controls. Aspects of the invention can bemodified to employ the systems, functions, and concepts of the variousreferences described above to provide yet further implementations of theinvention.

To reduce the number of claims, certain implementations are presentedbelow in certain claim forms, but the applicant contemplates variousaspects of an invention in other forms. For example, aspects of a claimcan be recited in a means-plus-function form or in other forms, such asbeing embodied in a computer-readable medium. A claim intended to beinterpreted as a mean-plus-function claim will use the words “meansfor.” However, the use of the term “for” in any other context is notintended to invoke a similar interpretation. The applicant reserves theright to pursue such additional claim forms in either this applicationor in a continuing application.

I claim:
 1. At least one non-transitory computer-readable storagemedium, carrying instructions, which, when executed by at least one dataprocessor of a system, cause the system to: determine a first geographiclocation, an azimuth, and a beamwidth of a sector antenna of a servingcell in a cellular network; determine a second geographic location of amobile device associated with a call served by the serving cell;determine a search area comprising an offset in degrees above and belowthe azimuth of the sector antenna; determine whether there is a firstneighbor cell in the search area; add the first neighbor cell to a listof eligible neighbor cells in response to determining that there is thefirst neighbor cell in the search area; in response to determining thatthere is no first neighbor cell in the search area, determine anexpanded search area by expanding the search area by the offset indegrees above and below the azimuth of the sector antenna, wherein theexpanded search area comprises an area that is less than or equal to thebeamwidth of the sector antenna; determine whether there is a secondneighbor cell in the expanded search area; add the second neighbor cellto the list of eligible neighbor cells in response to determining thatthere is the second neighbor cell in the expanded search area; determinea first distance comprising an average distance from the serving cell toone or more closest neighbor cells in the list of eligible neighborcells, wherein the first distance is determined based on the firstgeographic location and a geographic location of each of the closetneighbor cells; determine a second distance comprising a distance fromthe serving cell to the mobile device, wherein the second distance isdetermined based on the first and second geographic locations; when thesearch area is approximately equal to the beamwidth and no cells havebeen identified in the search area, so that the list of eligibleneighbor cells is empty, determine a default inter-site distance;determine that the serving cell is an over-shooter cell when the seconddistance is larger than the first distance or when the second distanceis larger than the default inter-site distance; and, automatically applyor cause to be automatically applied an electrical down-tilt or adecrease of a transmit power in response to determining that the servingcell is an over-shooter cell.
 2. The at least one computer-readablestorage medium of claim 1, wherein a number of the one or more closestneighbor cells is based on a density of cells in the cellular network.3. The at least one computer-readable storage medium of claim 1, whereinthe one or more closest neighbor cells is determined based on a numberof handovers or handover attempts between the serving cell and each cellin the list of eligible neighbor cells.
 4. The at least onecomputer-readable storage medium of claim 1, wherein the system isfurther caused to determine a priority indicator associated with theserving cell, wherein the priority indicator indicates the extent towhich the second distance is larger than the first distance.
 5. The atleast one computer-readable storage medium of claim 1, wherein a degreeof the electrical down-tilt or an amount of the decrease of the transmitpower is selected to cause an actual coverage of the serving cell tomatch a designed coverage of the serving cell.
 6. The at least onecomputer-readable storage medium of claim 1, wherein the system isfurther caused to: determine an elevation location data of the mobiledevice; determine a coverage in a lower elevation and a coverage in ahigher elevation based on the elevation location data, the firstdistance, the second distance, and a signal strength of the mobiledevice; and determine whether to apply an antenna down-tilt or up-tiltbased on the coverage in the lower elevation and the coverage in thehigher elevation.
 7. A method comprising: determining a first geographiclocation, an azimuth, and a beamwidth of a sector antenna of a servingcell in a cellular network; determining a second geographic location ofa mobile device associated with a call served by the serving cell;determining a search area comprising an offset in degrees above andbelow the azimuth of the sector antenna; determining whether there is afirst neighbor cell in the search area; adding the first neighbor cellto a list of eligible neighbor cells in response to determining thatthere is the first neighbor cell in the search area; determining whetherthere is a second neighbor cell in an expanded search area; adding thesecond neighbor cell to the list of eligible neighbor cells in responseto determining that there is the second neighbor cell in the expandedsearch area; determining a first distance comprising an average distancefrom the serving cell to one or more closest neighbor cells in the listof eligible neighbor cells, wherein the first distance is determinedbased on the first geographic location and a geographic location of eachof the closest neighbor cells; determining a second distance comprisinga distance from the serving cell to the mobile device, wherein thesecond distance is determined based on the first and second geographiclocations; when the search area is approximately equal to the beamwidthand no cells have been identified in the search area, so that the listof eligible neighbor cells is empty, determining a default inter-sitedistance; determining that the serving cell is an over-shooter cell whenthe second distance is larger than the first distance or when the seconddistance is larger than the default inter-site distance; and,automatically applying or causing to be automatically applied anelectrical down-tilt or a decrease of a transmit power in response todetermining that the serving cell is an over-shooter cell.
 8. The methodof claim 7, wherein a number of the one or more closest neighbor cellsis based on a density of cells in the cellular network.
 9. The method ofclaim 7, wherein the one or more closest neighbor cells is determinedbased on a number of handovers or handover attempts between the servingcell and each cell in the list of eligible neighbor cells.
 10. Themethod of claim 7, further comprising determining a priority indicatorassociated with the serving cell, wherein the priority indicatorindicates the extent to which the second distance is larger than thefirst distance.
 11. The method of claim 7, wherein a degree of theelectrical down-tilt or an amount of the decrease of the transmit poweris selected to cause an actual coverage of the serving cell to match adesigned coverage of the serving cell.
 12. A system comprising: at leastone hardware processor; and at least one non-transitory memory, coupledto the at least one hardware processor and storing instructions, which,when executed by the at least one hardware processor, cause the systemto: determine a first geographic location, an azimuth, and a beamwidthof a sector antenna of a serving cell in a cellular network; determine asecond geographic location of a mobile device associated with a callserved by the serving cell; determine a first distance comprising anaverage distance from the serving cell to one or more closest neighborcells in a list of eligible neighbor cells, wherein the first distanceis determined based on the first geographic location and a geographiclocation of each of the closet neighbor cells; determine a seconddistance comprising a distance from the serving cell to the mobiledevice, wherein the second distance is determined based on the first andsecond geographic locations; when the search area is approximately equalto the beamwidth and no cells have been identified in the search area,so that the list of eligible neighbor cells is empty, determine adefault inter-site distance; determine that the serving cell is anover-shooter cell when the second distance is larger than the firstdistance or when the second distance is larger than the defaultinter-site distance; and, automatically apply or cause to beautomatically applied an electrical down-tilt or a decrease of atransmit power in response to determining that the serving cell is anover-shooter cell.
 13. The system of claim 12, wherein a number of theone or more closest neighbor cells is based on a density of cells in thecellular network.
 14. The system of claim 12, wherein the one or moreclosest neighbor cells is determined based on a number of handovers orhandover attempts between the serving cell and each cell in the list ofeligible neighbor cells.
 15. The system of claim 12, wherein the systemis further caused to determine a priority indicator associated with theserving cell, wherein the priority indicator indicates the extent towhich the second distance is larger than the first distance.